• Korea journal of population studies
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• v.32 no.1
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• pp.139-164
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• 2009

The first demographic transition refers to the historical decline in mortality and fertility, as shown from the 18th Century in several European populations, and continuing present in most developing countries. The end point of the first demographic transition(FDT) was supposed to be a stationary and stable population corresponding with replacement fertility and zero population growth. In addition, households in all parts of the world would converge toward the nuclear and conjugal types, composed of married couples and their offspring. The second demographic transition(SDT), on the other hand, sees no such equilibrium as the end-point. Rather, new developments bring sub-replacement fertility, a multitude of living arrangements other than marriage, and the disconnection between marriage and procreation. Populations would face declining sizes if not complemented by new migrants. Over the last decades birth rates have been on the decline in all countries of the world, and it is estimated that already more than half of he world's population has below replacement level fertility. Measured in terms of the Total Fertility Rate (TFR), currently 34 countries have fertility levels of 1.5 or less. Similarly, Korea has been below lowest-low fertility for eight consecutive years since 2001 and below the replacement level for more than twenty years. In explaining the low fertility in Korea, some researchers explain the low fertility as revenge against a male-dominated society and institution, while others focus the impact of the employment instability. These studies share the basic ideas (spread of individualism, delayed marriage and childbearing, high divorce rate etc.) of a second demographic transition in order to explain the low fertility in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.105-114
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• 2017

The purpose of this study was to examine the effects of obesity at diagnosis on the prognosis of Korean breast cancer patients after classifying them according to their reproductive history and age by comparing the overall survival rate (OS) and disease-free survival rate (DFS). This study is a retrospective cohort study using 4181 breast cancer cases at one of the medical centers in Korea during the 3 year period from 2006 to 2008. We confirmed the levels of death and recurrence through a follow-up study completed in May 30. 2015. In conclusion, the parous patients had a lower OS than the non-parous patients (p=.000), and the younger patients below 40 years old had a lower OS and DFS than those who were 40 years old or older (p=.003, p=.000), while obesity did not affect the OS and DFS significantly. However, several subgroups in which obesity affected the OS and DFS were found after classifying the patients according to their reproductive history and age. For the subgroups classified by reproductive history, the obese patients had a lower OS and DFS than the non-obese patients in the subgroup in which the patients have a reproductive history (p=.001, p=.005). For the subgroups classified according to age, the obese patients had a lower OS and DFS than the non-obese patients in the subgroup in which the patients were 40 years old or older (p=.005, p=.014). Obesity affected the OS and DFS in the subgroup in which the patients were 40 years old or older and had a reproductive history (p=.000, p=.003). The results of this study show that obesity has an effect on the prognosis of breast cancer patients in the subgroups classified by reproductive history and age, whereas it has no effect on the OS and DFS of the patients when they are examined in their entirety. It also suggests that appropriate nursing intervention is needed for the subgroups in which obesity has effects on prognosis.

• Korea journal of population studies
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• v.29 no.2
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• pp.53-88
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• 2006

The major aim of this paper is to develop a hypothetical set of age-specific fertility rates which are logically derived and reasonably accurate in the projection of future population. The first procedure is to select a generalized log-gamma distribution model, which includes Coale-McNeil nuptiality model, in order to estimate and project a set of age-specific fertility rates by birth cohort and birth order. The second is to apply the log-gamma model with an empirical adjustment to the actual data to estimate and project the future fertility rates for relatively young birth cohorts who did not complete their reproductive career. This study reconstructs or translates a set of cohort age-specific fertility rates into a set of period age-specific fertility rates which must be hypothesized in order to establish the broader framework of future population projection. For example, the fertility at age 20 in the year of 2020 is the fertility at age 20 for the cohort born in 1990, while the fertility at age 21 in the year of 2020 is the fertility at 21 for the cohort born in 1989. In turn, once a set of age-specific fertility rates for the cohorts who were born up to the year of 2010, it is possible for one to establish an hypothetical set of period age-specific fertility rates which will be needed to project the future population until the year of 2055. The difference in the hypothetical system of age-specific fertility rates between this study and the 2005 special population projection comes from the fact that the fertility estimation/projection model used in this study was skillfully exploited to reflect better actual trend of fertility decline caused by rise in marriage age and increasing proportion of those who remain single until their end of reproduction. In this regard, this paper argues that the set of age-specific fertility rates derived from this study is more logical and reasonably accurate than the set of those used for the 2005 special projection. In the population projection, however, the fundamental issue of the hypothetical setting of age-specific fertility rates in relation to the fertility estimation/projection model is about how skillfully one can handle the period effects. It is not easy for one to completely cope with the problem of period effects except for the a minor period adjustment based on recent actual data, along with the given framework of a cohort-based fertility estimation/projection model.

• Korea journal of population studies
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• v.19 no.1
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• pp.45-72
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• 1996

The main purpose of this study is to analyze the level of fertility of Koreans in China in comparison to Hans. From the demographic perspective, this paper attempts to develop explanation for Korean immigration to northeast China since the mid 19th century. Of interest are the trend of population growth and geographic distribution of Koreans in China Attention is also given to the comparison of the demographic and socioeconomic characteristics between Koereans and Hans in China. The research is based on the raw data files of the 1990 Population Census from Jilin Province and Yanbian Korean Prefecture. The findings of the analysis suggest that the level of fertility of Koreans in China is substantially lower than those of Hans and other ethnic minority. This appears to be particularly true for Koreans residing in the regions densely populated with Koreans. The results of ANOVA and MCA confirm that the ethnic factor does have significant effects on the level of fertility. The lowest fertility of Koreans is found to be consistent after adjusting the effects of demographic and socioeconomic characteristics of the couple and the household. Despite the recent uprising of the sex ratio at birth in China, it is found in this study that the pattern of sex ratios for Koreans in Jilin Province and Yanbian Korean Prefecture has been fairly balanced and stable. Finally, Koreans are found to have higher level of child mortality than Hans and other ethnic minority.

• KDI Journal of Economic Policy
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• v.1 no.3
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• pp.131-146
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• 1979

• Clinical and Experimental Reproductive Medicine
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• v.2 no.2
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• pp.37-40
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• 1975

• KDI Journal of Economic Policy
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• v.1 no.1
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• pp.163-176
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• 1979

• Korea journal of population studies
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• v.4 no.1
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• pp.15-22
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• 1981

• Korea journal of population studies
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• v.5 no.1
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• pp.79-98
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• 1982

• Korea journal of population studies
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• v.10 no.1
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• pp.87-98
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• 1987